Substantial gaps exist between weed management researchers and practitioners with respect to prompt exchange of knowledge between the two groups, hindering the implementation of effective management to solve weed problems. We conducted a survey between 2016 and 2018 among weed management practitioners (n = 259) across diverse ecoregions on California rangelands and collected essential information from practitioners for bridging the research-implementation gap. The information included management costs, high-priority weeds, and spatial scales and temporal changes in weed management. The management cost had a mean of $5.12 ha–¹yr^–1 with a large variance implying the uncertainty of this information. The percentage of annual budget dedicated to weed management explained about 30% of the variation in this cost. Moreover, this annual per-unit area cost decreased with increasing management area. The average size of rangeland managed by survey respondents was 1 256 ha. The top three high-priority weeds statewide were yellow starthistle (Centaurea solstitialis), medusahead (Taeniatherum caput-medusae), and all thistles combined. Medusahead and some thistle species remained on the top list in each ecoregion. Respondents overwhelmingly (80.9%) noted changes in weed problems in the past 5–10 yr, specifically citing greater weed pressure and changes in weed species. A significantly higher proportion of respondents from agencies and private businesses reported changes in weed problems than those from universities and nongovernmental organizations (NGOs), further underscoring the gap between practitioners and researchers. A majority of the respondents (75.3%) indicated the record-setting California drought had a negative effect on weed management, reducing treatment efficacy and favoring weeds over desirable species. Overall, our findings illustrate increasing challenges in weed management on California rangeland. These challenges call for adaptive management-research programs to increase cost-effectiveness of weed management and to swiftly and effectively respond to dynamic weed problems on large spatial and long temporal scales.